WaveData was founded in 2000 to track the price changes taking place in the pharmaceutical market-place as imports arrived, patents expired and generic alternatives were launched.

It soon became apparent that there were patterns emerging in the price data relating to generic and off-patent products, but it took almost 6 years to gather enough data to allow us to investigate whether these patterns were purely random or whether there were other factors at work. This exercise involved in excess of 60,000 hours of work.

Initially, we found that the price decline curves we were recording were extremely variable; there appeared to be no easy explanation as to why one curve declined rapidly while another took years to erode to the same extent.

Our task, therefore, was to find a common set of denominators, which, with over 120 sets of post-expiry price data to analyse, became increasingly challenging.

We commenced this analysis by creating relationships between each declining price curve and some of the factors which may have influenced it – e.g. market value, reimbursement price, number of manufacturers, market share, etc.

Then came the highly complex task of linking these 120 formulae together, an undertaking which itself took many months of painstaking statistical work.

Eventually, however, we were able to discover a single statistical blueprint that regulated all the generic price decline curves that we had analysed.

The algorithm resulting from our statistical research, in mathematical terms, is a complex non-linear polynomial model, which intricately connects a range of underlying factors.

These factors themselves are not purely related to generic pharmaceuticals, but are both the causes and effects of wider market dynamics – we are talking, of course, about the laws of supply and demand.